[EMAIL PROTECTED] wrote:
>
> I am attempting to build a performance attribution model and have
> multicollinearity among my variables. As I would prefer not to remove
> variables, I am trying to program a PLS regression in SAS. I know from
> a previous posting that SAS has PROC PLS. MATLAB code to perform PLS.
You are trying to program PLS in SAS yet you also know SAS has PROC PLS?
Not clear to me what you mean. (It would have been clear to me if you
had said "I am trying to use PROC PLS..." but that's not what you said.)
> First, I need to know if this code will perform the regression using
> matrices. I believe Don Burrill posted this in a reply to a related
> question.
What matrices do you have? I believe that to perform PLS, you only need
a matrix X of the predictor variables and a matrix Y of the response
variables. You don't need any other matrices to get started. What code
are you referring to?
> Second, do I need to understand the PLS process to be able to program
> it in SAS, or can I just understand the inputs/outputs and be ok? (i.e.
> do I need to understand the black box to be able use it?)
If you are truly trying to write SAS code to program the PLS algorithm,
you probably need to understand the algorithm itself, as well as the
inputs and outputs. However, it makes no sense to me for you to program
it yourself as PROC PLS exists and works. And if you are going to use
PROC PLS (which isn't what you said), then you probably don't need to
understand the algorithm. You do need to understand what PLS does, why
it is the right technique (or a good technique) for your situation, and
you need to understand the outputs and be able to explain them to
non-statisticians.
If you view it as a "black box", which means to me that you throw in
some data and get some results without understanding why, then you are
probably headed for troube.
--
Paige Miller
Eastman Kodak Company
[EMAIL PROTECTED]
"It's nothing until I call it!" -- Bill Klem, NL Umpire
"Those black-eyed peas tasted all right to me" -- Dixie Chicks
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